5 papers · 1 filter
Factors in Crowdsourcing for Evaluation of Complex Dialogue Systems
Annalena Aicher, Stefan Hillmann, Isabel Feustel +3
In the last decade, crowdsourcing has become a popular method for conducting quantitative empirical studies in human-machine interaction. The remote work on a given task in crowdwo…
Anchored Alignment for Self-Explanations Enhancement
Luis Felipe Villa-Arenas, Ata Nizamoglu, Qianli Wang +2
In this work, we introduce a methodology for alignment designed to enhance the ability of large language models (LLMs) to articulate their reasoning (self-explanation) even in the…
Cross-Refine: Improving Natural Language Explanation Generation by Learning in Tandem
Qianli Wang, Tatiana Anikina, Nils Feldhus +3
Natural language explanations (NLEs) are vital for elucidating the reasoning behind large language model (LLM) decisions. Many techniques have been developed to generate NLEs using…
CoXQL: A Dataset for Parsing Explanation Requests in Conversational XAI Systems
Qianli Wang, Tatiana Anikina, Nils Feldhus +2
Conversational explainable artificial intelligence (ConvXAI) systems based on large language models (LLMs) have garnered significant interest from the research community in natural…
LLMCheckup: Conversational Examination of Large Language Models via Interpretability Tools and Self-Explanations
Qianli Wang, Tatiana Anikina, Nils Feldhus +3
Interpretability tools that offer explanations in the form of a dialogue have demonstrated their efficacy in enhancing users' understanding (Slack et al., 2023; Shen et al., 2023),…